Product dynamics and Trade liberalization: Evidence from US-Korea FTA

Transcription

1 Very preliminary and all comments are welcome. Product dynamics and Trade liberalization: Evidence from US-Korea FTA Jung Hur * Haeyeon Yoon Abstract This paper analyzes both the quantitative and qualitative changes of firms product mix in response to trade costs reductions by using Korean plant-level data. We find that exporting firms churn their product mix actively and expand product scope relative to domestic firms in response to Korea-US Free Trade Agreement of The degree of tariff reductions do not induce significantly differential responses to non-exporting firms, while exporters experiencing large tariff reductions are more likely to add products and increase product scope relative to exporters with small tariff reductions. Furthermore we examine the characteristics of added and dropped products to investigate the direction of firms resource reallocation. Different from the previous study, we measure firm-product efficiencies by estimating multi-products production function. Our results show that firms tend to add and drop less efficient products than the firms average in response to tariff reductions. Also, firms hold products having industrial relations with core products, while they switch products which are not included in same or vertically related industry with that of the core. Key words: Multi-product firms; Product mix; Product scope; Tariffs; KORUSFTA; JEL classification: F10; F15; L11; L25; * Department of Economics, Sogang University; Hitotsubashi Institute for Advanced Study, Hitotsubashi University, ecsjhur@sogang.ac.kr Department of Economics, Sogang University, hyyoon@sogang.ac.kr 1

2 1. Introduction As entry and exit of firms contribute to resource reallocation within-industry, firms reassign resources by adding and dropping their product. The majority of multi-product firms in production and the frequent product churnings highlight an importance of product dynamics in economies (Bernard et al., 2010; Goldberg et al., 2010). To gain a better understanding of firms product churning behavior, researchers have studied how firms restructure their product mix in response to trade cost changes. But since the bilateral trade cost reductions increase market competition in home country and also market access to foreign country, the net effects depend on the relative size of the two opposite effects. Therefore firms responses to trade cost changes are heterogeneous upon firms productivity, size, or export status (Baldwin and Gu, 2009; Dhingra, 2013; Qiu and Zhou, 2013). The heterogeneous responses suggest that the productive firms utilize the increased access to foreign market actively, while the less productive firms have not enough abilities to take advantage of the opportunity. To understand the product churning and resource reallocation within firm deeply, Bernard et al. (2010) investigated the characteristics of dropped products and found that the dropped products size and tenure are relatively small. But for the subject of resource reallocation, a product efficiency is more proper to be examined than the dropped product size and tenure. Also, the characteristics of added products have to be analyzed to understand the process and the direction of product churning. But the previous literatures are silent about it. In an attempt to deepen an understanding of product churning patterns, this paper investigates how Korean manufacturing firms react to trade cost reductions. In 2012 in relation with Korea- US Free Trade Agreement (FTA), a large change occurred in the Korean trade environment which should have affected the firms product mix. Referring that US is the Korea s 2 nd largest export market and the 3 rd largest import market in 2011, the effects of Korea-US FTA (KORUS 2

3 FTA) on Korean firms are expected to be larger than the other FTAs in Korea 1. Figure 1 shows the trend of average US tariff rate against Korean manufacturing imports (solid line) and mostfavored-nation tariff rate (dashed line) in the period In 2011, the average US tariff rate against Korea was 3.50 percent. The tariff rate sharply decreased according to KORUS FTA and reached 0.85 percent in 2013 falling by 76% from 2011 to The tariff rate has decreased gradually even after 2013, but the largest decline occurs in 2012 when KORUS FTA comes into effect 2. Also, according to Article 2.10 of the Free Trade Agreement, both countries eliminate any administrative fee for trade 3. The KORUS FTA is not only limited to the trade of goods, but also creates new market access on investment, telecommunications, express delivery, and legal consulting services. Clauses on national treatment to investors are written in Article Furthermore, given that both China and Japan which are the major competitors of Korea s exports to US do not sign a FTA with the US, for Korea the KORUS FTA creates substantial new market access opportunities and strengthens ties with US. Given the importance of US to Korean trade and substantial reductions of trade costs between the two countries in 2012, we will examine the firms product churning between 2011 and 2013 years. After the KORUS FTA, the trade shares of Korea and US in each country slightly increased between 2011 and 2015; the Korean share in US imports raised from 2.6% to 3.2% and the US 1 Following the FTA with Chile in 2004, Korea has actively contracted FTA with several trade partner countries. At June 2018 Korea is running 16 FTAs; Chile in 2004, Singapore in 2006, Island, Liechtenstein, Norway and Switzerland in 2007, ASEAN (Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand and Vietnam) in 2007, India in 2010, Peru in 2011, US in 2012, Turkey in 2013, Australia in 2014, Canada in 2015, China in 2015, New Zealand in 2015, Vietnam in 2015, EU (Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherland, Poland, Portugal, Romania, Spain, Slovakia, Slovenia, Sweden, and United Kingdom) in 2015, and Colombia in Even if Korea and China FTA came into effect in 2015, the largest exporting and importing market for Korea, since 2017 data is not available the effects of China-Korea FTA on firms product churning could not be investigated in this study. 2 The Korea-US FTA took effect on March 15 th Article 2.10 is written as "Neither Party require consular transactions, including related fees and charges Neither Party may adopt or maintain a merchandise processing fee on originating goods.". 4 US treats investments from Korea same as those from in-state investors. 3

4 share in Korea imports increased from 8.5% to 10.1%. Even though the quantitative changes in trade are not substantial, over the same period the number of exported products from Korea to US had increased by 9.7% from 5,541 to 6,081. The large reduction in tariff rate affects price, costs, and competition faced by firms and then it induces firms to churn their product mix. Since the input resources are utilized to manufacture goods, the product dynamics indicate the resource reallocation and qualitative changes within firms. Referring that firms mainly demand and assign resources in economies, to examine the resource reallocation upon trade costs changes firm-product studies are needed by investigating how firms reorganize their product portfolio. [Figure 1] Using Korean plant level data, we investigate how firms restructure their product mix in response to the bilateral tariff reductions. First, we examine the firms decision on product adding and dropping and then changes in firms product scope and diversification. Considering the two effects of trade cost reductions, we separately analyze the exporting firms which may utilize the opportunity of increased foreign market access fully compared to the non-exporting firms. After seeing the firms response to tariff reductions, we examine the characteristics of switched products relative to other products within the same firms. For product characteristic variables, we utilize products relative size, efficiency, tariff reductions and industrial relation of the firms core products. Different from the previous studies, we directly measure firmproduct efficiencies by using the estimation method of multi-product production function from Dhyne et al. (2017). Since product churning and resource reallocation include both adding and dropping activities, this paper analyzes not only dropped products but added products also. Therefore this study contributes to the literature by investigating not only the quantitative changes but also the qualitative changes of firms product mix in response to tariff reductions. 4

5 Our results show that the degree of tariff reductions does not induce significantly different effects on firms product churning and scope. But we find the heterogeneous responses of firms upon their export status; exporters are active at adding and dropping products and increase their product scope relative to non-exporting firms. Also, exporters which experience larger tariff reductions have higher probabilities of adding products and increasing their product diversification than those with smaller tariff reductions. The heterogeneous responses between exporting and non-exporting firms indicate the existence of two opposite effects from trade cost changes. The exporting firms may be more competitive in domestic market and utilize the better market access to foreign country more efficiently than non-exporting firms. The estimation results about added and dropped products characteristics give hints on how firms adjust their product mix in response to trade costs reductions. We found that firms tend to add and drop small and inefficient products relative to other products within the same firms. Also, products which have not industrial relation with the firms core products show higher exit and entry rates than other products industrially related with the core products. The empirical results support the theoretical model about firms specialization in core competence (Eckel and Neary, 2010). This paper is organized as follows. Section 2 reviews the related literatures. Section 3 describes data and brief summary statistics of Korean multi-product firms. Sections 4 focuses on the estimation of firms response to tariff reductions. Section 5 analysis which products are added and dropped following trade cost reductions. Section 6 concludes. 2. The Literature The literature about product churning has expanded with the increased availability of firmproduct level data and the finding of multi-product firms economic importance. Bernard et al. 5

6 (2010) find that in US 39 percent of manufacturing firms produce more than two products and those firms account for 87 percent of total manufacturing output. The prevalence and importance of multi-product firms are also shown in a developing country context, like India 5 (Goldberg et al., 2010). It should be noted that the active product churning is not limited to the multi-product firms, but also single-product firms switch their product mix as well. More than half of manufacturing firms add or drop their product and the firms with large output are more active in product churning than those with small output level (Bernard et al., 2010; Goldberg et al., 2010). In order to have a better understanding of how firms organize their product mix, several studies have examined the response of firms on trade cost changes. However, the empirical results of firms response are found to be quite different across the literatures. For instance, Bernard et al. (2011) show that US manufacturing firms which experience above-median tariff reductions through Canada-US FTA decrease their product scope relative to firms experiencing below-median reductions. While Baldwin and Gu (2009) report that the bilateral tariff reductions between Canada and US make small firms to decrease their product scope, but it does not cause any significant effects on large firms in Canada. Using Mexican firm data, Iacovone and Javorcik (2010) find that most of firms in Mexico add new products for export when the North American Free Trade Agreement came into effect. The different empirical results are from the simultaneous two opposite effects of tariff reductions; rising competition in home market and allowing better access to foreign markets. Since the two effects could offset each other, the tariff reductions effect on product churning and scope may depend on their relative sizes. If a firm is competitive enough or is able to utilize the foreign market access 5 Indian multi-product firms account for 47 percent of manufacturing firms and 80 percent of manufacturing output. 6

7 opportunities, then the firm s product scope will increase. So only productive firms (Dhingra, 2013; Qiu and Zhou, 2013) or foreign-oriented firms (Lopresti, 2016; Nocke and Yeaple, 2014) will expand their product scope in response to the bilateral tariff reductions. In this study, we will empirically check the different responses of firms on product mix according to their export activity. The ultimate objective of study on product churning is attributed to the desire to know how firms reallocate their resources in response to possible tariff reductions. Several theoretical studies investigate the mechanism of firms decision concerning product switching. Most of them predict that firms will specialize in their core competence in response to the trade cost reductions and the increased competition in domestic market (Bernard et al., 2011; Eckel and Neary, 2010; Mayer et al., 2011). These studies feature within firm difference in production cost by defining a core product which has the lowest marginal cost. According to the model, firms will expand their product scope from the core product, since the farther distance from the core product means the larger marginal costs. Therefore, if home market shocks occur, firms are more likely to drop peripheral products which has the highest marginal cost. Several empirical studies find the firms skewedness tendencies to the core product and the higher exit rate of peripheral products (Bernard et al., 2010; Liu, 2010; Ma et al, 2014). As proxy variables for product competence, they utilize the relative product sales by assuming that the core product takes the largest portion of sales. But the relative size does not precisely capture the products competence within firm. Different from the previous studies, this paper measures a firm-product efficiency directly and investigates how firms churn their product mix when US decreases the tariff rates on Korean manufacturing imports. Investigating the characteristics of added and dropped products will give hints on how firms reallocate their resources. We estimate a multi-product production 7

8 function and measure firm-product efficiencies following Dhyne et al. (2017) s approach. Using Belgian firm level data, Dhyne et al. (2017) estimated firm-product technical efficiencies based on models of Diwer (1973) and Lau (1976). De Loecker et al. (2016) and Foster et al. (2008) also estimated the firm-product efficiencies but they utilized single-product production function by allocating firms input to each product in the proportion process to the product s revenues share (Foster et al., 2008) or utilizing input optimization (De Loecker et al., 2016). The multi-product production function is different from the single-product production function case in that it considers the production of other products within the same firm. Since our data includes product churning of multi-product firms, we utilize the estimation method of multiproduct production function. By using the firm-product efficiencies, we are able to investigate whether firms add and drop less efficient products relative to other products within the same firms or not. Additionally, industrial linkages between the added or dropped products and the core one are examined. 3. The Data To investigate within-firm product churning, we utilize Korean plant-level data, the Mining and Manufacturing Survey (MMS) from Statistics Korea for the period except for the years 2010 and The Statistics Korea annually surveys plants in Korean mining and manufacturing sectors with at least 10 workers. The MMS includes information on plant s output, inputs, and its firm s identification number (ID). The output information includes the set of products that plants produce and the sales of each product. Since the information on plant s export activity is not included in the MMS, we additionally utilize the plant s export 6 The Statistics Korea does not announce MMS when Economic Census is surveyed, since all plants in MMS are included in the Economics Census. 8

9 data obtained from the Korea Customs Service. The custom data gives the ID of plant which has positive amount of export. By combining the two data sets through matching the plant s ID, we could identify exporting plants. The decisions about product mix and resource reallocation tend to be made at the firm level rather than the plant level, so we aggregate the plants information to firms by using the ID of firms which the plants belong to. To investigate Korean firms response when US reduced its tariff rates against Korean imports, we firstly analyze and measure product dynamics and tariff changes. Before introducing an empirical model, we examine briefly the characteristics of multi-product firms and product churning in Korea. In doing so, we define a product as 8-digit KSIC (Korea Standard Industry Classification) category. The firms which produce more than 2 different products are called multi-product firms, while the other are single-product firms. The 4-digit and 2-digit KSIC categories are used to define industry and sectors, respectively. According to those definitions, Korean manufacturing consists of 24 sectors, 180 industries, and 2,139 products 7. By employing the abovementioned definitions, in Table 1 we examine the prevalence of multiproduct, industry, and sector firms in the period , except for the years 2010 and The Multi-product firms account for 16% of Korean manufacturing firms and 70% of manufacturing output. Even if the number of multi-product firms is small, the firms explain a large portion of the economy in Korea. The last column of Table 1 indicates that multi-product firms produce 2.66 products on the average. The multi- industry and multi- sector firms account for only 10% and 6% of firms, but they produce 59% and 49% of output, respectively. [Table 1] In order to investigate the characteristics of multi-product firms, we compare the firm 7 In the study by Bernard et al. (2010), US manufacturing is composed of 20 sectors, 455 industries, and 1,440 products. 9

10 characteristics of single- and multi-product firms by regressing the natural log of characteristics on the multi-product (industry or sector) firm dummy with 4-digit level industry fixed effect. As the characteristics variables, output, number of full-time workers, labor productivity measured as the share of revenue per employee, and total factor productivity (TFP) based on revenue from Cobb-Douglas production function with two-third labor share are used 8. Table 2 reports the coefficients of multi-product (industry or sector) firm dummy variable in each regression case. The estimation results show that multi-product firms are larger and more productive than single-product firms in the same 4-digit level industry. [Table 2] To see how firms organize their product mix, in Table 3 we examine the distributions of products within-firm. In the last column, we merge all firms producing more than 10 products into one group. The distribution of sales across products is skewed towards firm s core product. The largest product takes more than 70 percent of sales for firms with 2 products and the share decreases gradually to 40 percent for firms with 9 products. The distributions of products except for the largest one are relatively constant across the number of products produced by the firms. [Table 3] In Table 4, we examine the activeness of product churning in Korean manufacturing firms by separating firms into 4 groups. The sample is restricted to firms which survive both 2011 and First, if firms neither add nor drop products between 2011 and 2013, then they are categorized into None group of firms. Second, firms which only drop or only add products are included in Drop only and Add only groups, respectively. Lastly, firms both adding and 8 The revenue and capital variables are converted into real terms by using 2-digit industry level deflator index from the Bank of Korea. 10

11 dropping products are classified as Both group. In other words, the firms which are not included in None group churn their product mix between the years 2011 and Table 4 describes firms product churning activity in Panel A and that of weighted by firms output in Panel B. The first column in Panel A shows that on average 22.7 percent of Korean manufacturing firms churned their product portfolios between 2011 and Among them, 2.8 percent of firms only drop products, 3.7 percent of them only add new products, and 16.1 percent of firms both drop and add products in the study period. Exporters are more active in product churning by showing that 27.7 percent of them switch their product mix. Multi-product and multi-plant firms are more likely to add or drop their products compared to single-product and single-plant firms counterparts, respectively. Firms with more than 100 workers are the most active groups in product churning. When we employ weights using output share in Panel B, the share of firms which switch their product mix is much larger than that before weighted. The results in Panel B indicate that firms with large shares of output add and drop products more actively than those with small output shares. [Table 4] For tariff data, we utilize US tariff rates on Korean manufacturing imports obtained from U.S. International Trade Commission (ITC). The tariff rates are reported in an 8-digit Harmonized Tariff Schedule of the United States (HTS-US) code. We aggregate the 8-digit level tariff into 6-digit level by using 8-digit US imports from Korea. For example, Electrical lighting or visual signaling equipment for use on bicycles (HTS ) consists of Electrical lighting equipment (HTS ) and Electrical visual signaling equipment (HTS ). The tariffs on Electrical lighting equipment (HTS ) and Electrical visual signaling equipment (HTS ) in 2011 are 0% and 2.7%, respectively. The US imports for the two products from Korea in 2011 are 19 and 0 (1,000 US dollar) each. So the weighted average 11

12 tariff rate for Electrical lighting or visual signaling equipment (HTS ) in 2011 is zero (0* * 0 ). Since the tariff rate from U.S. ITC and the product data in MMS are reported in two different classification codes; HTS and KSIC, we match the 6-digit level HTS code to the 5-digit level KSIC code 9. Figure 2 shows the distribution of products tariff rates in year 2011 and tariff changes between 2011 and Most of the products tariff rates reductions are concentrated in the ranges of - 5 and 0 percentage points. The negative slope between tariff rates in 2011 and rates of tariff changes indicates that the products facing high level of tariffs before the KORUS FTA experience relatively large reductions. [Figure 2] With the product level tariff rates data, we measure the sales weighted average of tariff reduction subjected firm i between 2011 and 2013 written as: (1) Tariff i = share 2011 j ij Tariff j, where share 2011 ij is the share of 5-digit level industry j s sales in firm i at year Tariff j represents the US tariff rate changes against Korean manufacturing imports in industry j between 2011 and Since all products produced by firm i do not experience the same tariff changes, the weighted average tariff reductions may catch the difference of changes well considering each product s importance in the firm. On averages, firms experience 1.74 percentage points of tariff rate reductions between 2011 and The largest tariff rate change is percentage points. 9 Since the first six digits HTS code take the same form as those of Harmonized System (HS) code, we are able to match the 6-digit HS code to the 5-digit KSIC code. 12

13 4. Empirical Evidence Within-Firm Product Churning To see the firms product churning in the period of KORUS FTA application, we examine firms decision on product adding or dropping in response to US tariff reductions. Equation (2) reports the estimation model of within-firm product churning in response to tariff changes expressed as: (2) Y it = b 0 + b 1 Tariff it + b 2 Export it 1 + b 3 ( Tariff it Export it 1 ) + b 4 ln(tfp it 1 ) + γ k + e it where Y it takes the value 1 if firm i adds (or drops) a product before and after KORUS FTA; otherwise it takes the value of 0. Tariff it is the change in firms weighted tariff rate between the years 2011 and Since the bilateral tariff reductions induce two opposite effects; rise of competition in home market and access to foreign markets (Bernard et al., 2011), the net effects could be insignificant. In order to investigate the different effects we utilize an export dummy variable, Export it 1, which take the value of 1 if firm i does export in year 2011, since exporters may be more exposed to the market expansion effects than domestic firms. As control variables, a firm i s total factor productivity measured by Cobb-Douglas production function in year 2011, ln(tfp it 1 ), is included. γ k represents firm i s main 4-digit level industry k dummy variables. e it is standard errors clustered by 4-digit industry. [Table 5] 10 Instead of the tariff change variables, we also utilize a dummy variable representing whether tariff reductions faced by firms are above or below average tariff reductions following the Bernard et al. (2011) s method. The results with the tariff reductions dummy variable are similar to those in Table 5 and 6. However, the interaction term between the tariff reductions dummy and export dummy variables turned out to be statistically insignificant. 13

14 Table 5 describes the firms product churning in response to US tariff reductions against Korea imports. The dependent variable in columns (1)-(3) of Table 5 takes the value of 1 if a firm adds new products between 2011 and The coefficients of tariff change variables show that firms product adding decisions are not significantly associated with the degree of tariff reductions. But exporting firms have a higher probability of adding new products then domestic firms when the US tariff against Korea decreases sharply. In column (3), we add an interaction term between the variables of tariff changes and exporter dummy. The coefficient of interaction term is negative and statistically significant at the 1 percent level. A one percentage point reduction in firms tariffs is related to a 0.8 percent rise in the probability of adding products by exporters. The effects of trade cost changes on firms product dropping decision are shown in columns (4)-(6) of Table 5. In similarity with firms product adding decision, there are no significant differences in product dropping decision between firms experiencing large and small tariff reductions. And exporters which may utilize the rising market access opportunity efficiently show higher product dropping rates than domestic firms. But even among exporters the degree of tariff reductions are not systematically associated with their production dropping decisions. Table 5 shows that exporters actively churn their product relative to domestic firms. The results indicate a differential response to trade cost reductions among firms according to their foreign market involvement. However, the product churning decisions are found not to be significantly related to the degree of tariff reductions. Firm s Product Scope In Table 6, we examine the effects of trade cost reductions on the changes of firms number of products and product diversification. The diversification is a Herfindahl-Hirschman style index 14

15 measured as one minus the summation of squared products sales share within firms 11. The estimation model in equation (3) is similar to that in the equation (2). (3) ΔY it = a 0 + a 1 Tariff it + a 2 Export it 1 + a 3 ( Tariff it Export it 1 ) + a 4 ln(tfp it 1 ) + a 5 Y it 1 + γ k + e it The dependent variable, ΔY it, is the difference in the number of products produced by firm i (or product diversification of firm i) between 2011 and Firm i s number of products (or product diversification) in 2011, Y it 1, is included as an independent variable, with the firms tariff changes degree, exporter dummy, interaction term of those two variables, productivity, and industry dummy variables. e it represents clustering standard errors on industry. [Table 6] The changes in number of products are examined in columns (1)-(3) of Table 6 and in columns (4)-(6) the changes in product diversification are investigated. The coefficients of tariff reduction degree variable are positive but not statistically significant in all columns. It indicates that the variation of tariff reductions that firms experience do not give significantly different effects on the changes in the number of product and product diversification. In column (2) and (5), we investigate the difference in the tariff cuts effects between domestic and exporting firms. The results show that exporting firms increase their number of products and product diversification relative to domestic firms. The interaction terms in column (3) and (6) show that for exporters the more tariff reductions the firms experience the higher increases in product scope the firms have. But the effect on the number of products is not statistically significant. In Table 6, we found that exporters expand their product scope both in the product range and 11 Diversification it = 1 P ( Sales pit product p (p=1,, P). p=1 P p=1 Sales pit 2 ) is the diversification index of firm i at year t which produces 15

16 product distribution relative to non-exporters when they experience large reductions in tariff through the KORUS FTA. Similar to product churning, the degree of tariff reductions do not give significantly different effects on the changes of firms product scope, while exporters experiencing larger tariff reductions increase their product diversification more but not their product range. With Table 5 and 6, we examine how Korean firms respond to tariff changes between 2011 and The results show that within firm product churning and product scope changes seem to be not significantly associated with the degree of tariff cuts. As mentioned above, the bilateral trade cost reductions increase the competition in domestic market and the access to foreign markets also. So the insignificant effects may be from offsetting the two opposite effects. It does not indicate that firms do not respond to the US tariff reductions against Korea, but only indicate that the relation between the degree of tariff reductions and product churning is not statistically significant. We also found evidence of differential effects of tariff reductions between domestic and exporting firms. The exporting firms show active product churning by both adding and dropping their products and they increase the number of their products and product diversification relative to domestic firms. Since the exporting firms could make good use of market expansion opportunity relative to the domestic firms, they are more likely to switch their product-mix, reallocate resources, and expand product scope when large bilateral tariff reductions occur. In the next session, we will analyze switched products characteristics to investigate the firms response to tariff cuts in detail. 5. Further Study In this session, we examine the characteristics of added and dropped products with 5 variables indicating property of the products. The first variable is a relative size of product measured by 16

17 the log difference of a product s sales and average products sales within-firm. The relative size variable is generally used as proxy variable for a product efficiency. Instead of the proxy variable, secondly, we measure the firm-product efficiencies. Following Dhyne et al. (2017), we utilize multi-product production function as shown in equation (4): (4) y pit = β p 0 + β p l l it + β p k k it + β p p m m it + γ pit y pit + e pit Where y pit is sales of product p in firm i at year t. l it, k it, and m it denote the labor, capital, and material inputs of firm i. Since in multi-product firms the sales of product p not only depend on firm i s total inputs but also other products, the estimation includes a vector of all other products sales in firm i excluding product p s, y pit. e pit is composed of specification error, n pit, and efficiency shock, w pit. We estimate the efficiency using the multi-product production function from Dhyne et al. (2017). Since the number of observations per a production mix is limited, we pool the estimation at the 3-digit product level. In our estimation, l it is the number of full-time worker, k it is the tangible fixed asset and m it is the material inputs of firm i. k it and m it are deflated with a 2-digit level industry deflator from the Bank of Korea. After estimating each product s efficiency, we measure the average products efficiencies in a firm. Since we compare the efficiencies of products within firms, we construct a relative efficiency dummy variable which takes the value 1 if product p in firm i has lower efficiency than the firm i s average efficiency; otherwise it takes 0. We report the results of multi-product production function estimates in Appendix. Table A1 describes the estimation results of top 10 products according to the number of firm-product observations. All the coefficients of input factors are positive and those of other products sales are negative According to the models of Diewert (1973) and Lau (1976), the sale of product p is non-decreasing in input factors holding the sales of other products(-p) constant and it is non-increasing in the sales of other product (-p) holding input constant 17

18 The third product property indicator variable is a relative tariff change dummy variable which takes the value of 1 if the tariff reduction of product p is larger than that of its firm, otherwise it takes the value 0. The fourth and fifth variables are related to relation between product p and its firm s core product. A same industry dummy variable represents whether product p has the same 4-digit level industry code with the firm s core product. Lastly, a vertically relatedness dummy variable is 1 if product p s industry is vertically related to that of core product. The vertical relation is measured with 2010 Input-Output tables from the Bank of Korea. We define industry i and j are vertically related if the industry i (or j) s share of intermediate goods expenditure on j (or i) is more than 10 percent 13. [Table 7] Table 7 represents the summary statistics of the 5 product characteristic variables. The negative mean value of the relative size variable shows the specialization of firms production. About 11.8% of products have lower efficiencies than the averages of their firm-product s efficiencies. More than 80% of products experience larger tariff reductions than their firms weighted average tariff cuts. About 60% of products are included in same industry with the core products and 19% of products are vertically related with the core products. [Table 8] The previous studies treat the product s relative size as a firm-product efficiency and predict that the peripheral products may have a little relation with the core product (Bernard et al., 2010; Liu, 2010; Ma et al., 2014). A key challenge in empirical estimation is how to measure the proximity or distance between a product and the core product in the same firm. The products in proximate industry or in vertical relation with the core may have high efficiencies relative 13 Even if we restrict the threshold from 10 to 5 or 1 percent, the estimation results do not change. 18

19 to the others, since the core competence could be modified and applied to the products in related industries. In order to examine the relations, we estimate the correlation among the relative size, relative efficiency dummy, same industry dummy, and vertical relatedness dummy variables in Table 8. The negative relation between relative size and relative efficiency dummy variables indicates that a product with relative large size may have higher efficiency than the average products efficiencies of its firm. The sign of correlation between the efficiency dummy and industrial relation dummy variables fits the prediction presented above. Products in same or vertically related industry with that of the core product seem to have higher efficiencies relative to other products in the same firms. To investigate which products a firm adds or drops between 2011 and 2013, we estimate the model in (5) specified as: (5) Y pi = c 0 + c 1 x pi + γ p + δ i + e pi The dependent variable, Y pi, in Table 9 (Table 10) takes the value of 1 if product p in firm i is dropped (added) following the sharp tariff reductions. x pi is a characteristic variable of product p in firm i at year 2011 (2013); relative size, relative efficiency dummy, relative tariff reductions dummy, same industry dummy, or vertical relatedness dummy variables. Product, γ p, and firm, δ i, fixed effects are employed to capture unobservable firm and product effects. e pi is standard errors clustered by 8-digit level product. [Table 9] Table 9 examines the characteristics of dropped product. The negative coefficient of relative size variable indicates that firms drop products taking small portions of sales in firms and specialize in their core products. Different from the previous studies, we estimate firm-product efficiencies and construct the relative efficiency dummy variable showing whether product p 19

20 in firm i has a lower efficiency than the average products efficiencies in the same firm or not. In column (2) of Table 9, the coefficient of relative efficiency dummy variable is positive and statistically significant at the 1 percent level. The result is interpreted as a product with lower efficiency than those of its firm s average has a higher probability to be dropped in the firm s product mix. In column (3), we investigate the effects of relative tariff reductions degree on the product s exit rate. Whether a product s tariff reduction is larger than that of its firm does not have a significant effect on its product exit rate. The results in columns (4) and (5) indicate that products included in same or vertically related industry with the core products show lower exit rate than the other products. In Table 9, we find that firms have propensity to drop relatively less efficient products within their product mix and drop less associated products with the core product in response to trade cost reductions. [Table 10] In Table 10, we investigate the characteristics of added products. The added products have small size and low efficiencies relative to their firms average value of size and efficiency. The results support the prediction of Eckel and Neary (2010) s model which argues that firms have tendency to switch peripheral products with higher marginal cost rather than core products. The coefficient in column (3) shows that firms more likely add products which experience larger tariff reductions than the firms average. The results in columns (4) and (5) indicate that the added products tend to have no industrial relations with the core products in their firms. With Table 9 and 10, we find that firms add and drop products which have small size and low efficiencies relative to the firms average. The added and dropped products are more likely to have low industrial proximity to the core product. Referring to the correlation between the relative efficiency dummy and industrial relation variables in Table 8, the results indicate that firms switch products with lower efficiencies than those of other products within the same firms 20

21 and those far distanced from their core products. In other words, the firms do not seem to touch their core products when churning their product portfolios in response to trade cost reductions. 6. Conclusion Following the conclusion of the FTA, US had decreased the tariff against Korean manufacturing imports by 76% between 2011 and This paper examines how firms adjust their product mix in response to trade cost reductions initiated by trade partner following free trade agreements, using the Korean manufacturing firm data between the years 2011 and Firstly, we find that exporters actively churn their product mix and expand product scope relative to domestic firms. The product churning and product scope seem not to be affected by the degree of tariff reductions that firms experience. But exporters experiencing large tariff reductions are more likely to add new products and increase their product diversification relative to exporters subjected to small tariff reductions. The heterogeneous responses of firms suggest that the net effects of trade costs reductions depend on the relative size of the two opposite effects, namely rise in domestic competition and foreign market access. The export firms which may utilize the foreign market access opportunities effectively churn their product portfolio more and broaden their product scope relative to the domestic firms. Furthermore, we investigate specifically which products the firms add and drop in response to tariff reductions. Different from the previous literatures, we estimate firm-product efficiencies through multi-product production function and examine whether firms drop or add relatively less efficient products or not. Including the products efficiencies, we also investigate the products relative tariff reductions and industrial relation with firms core products. We found that smaller and less efficient products within firm are more likely to be dropped and 21

22 products included in same or vertically related industry with the core products show lower exit rate than the other products having no industrial relation with the core product. The added products are not larger or more efficient than those of average firm-products and they are less likely to have industrial relation with core products. Those results seem to support a model highlighting core competence and specialization in firms product scope (Eckel and Neary 2010). The relative products tariff reductions do not give any significant effects on product dropping, while firms tend to add new products which experience larger reductions than firms averages. This paper contributes to the literature as investigating both firms product churning and product scope, and also the characteristics of product mix with several products characteristic variables. From the results we could suggest how firm adjust their product mix and scope, and also how firm reallocate their resources. Also our empirical results about firms responses on trade costs reductions have political relevant contributions in regards to the rise of protectionism in the world these days. The strengthened protectionism will induce firms to restructure their product mix in the opposite way from that in trade costs reductions. 22

23 References Baldwin, J. and W. Gu (2009), The Impact of Trade on Plant Scale, Production-Run length and Diversification, in Producer Dynamics: New Evidence from Micro Data, ed. T. Dunne, J. B. Jensen and M. J. Roberts (Chicago: University of Chicago Press). Bernard, A. B., S. J. Redding, P. K. Schott (2010), Multiple-product firms and product switching, American Economic Review, 100, Bernard, A. B., S. J. Redding, P. K. Schott (2011), Multiproduct firms and trade liberalization, Quarterly Journal of Economics, 126, De Loecker, J., P. Goldberg, A. Khandelwal, and N. Pavcnik (2016), Prices, markups and Trade Reform", Econometrica, 84, Dhingra, S. (2013), Trading away wide bands for cheap brands, American Economic Review, 103 (6), Dhyne, E., A. Petrin, V. Smeets, and F. Warzynski (2017), Multi Product Firms, Import Competition, and the Evolution of Firm-product Technical Efficiencies, Unpublished Working Paper. Diewert, W. (1973), Functional Forms for Profit and Transformation Functions, Journal of Economic Theory, 6, Eckel, C. and J. P. Neary (2010), Multi-Product Firms and Flexible Manufacturing in the Global Economy, Review of Economic Studies, 77, Forster, L., J. Haltiwanger, and C. Syverson (2008), Reallocation, Firm Turnover, and Efficiency: Selection on Productivity or Profitability?, American Economic Review, 98,

24 Goldberg, P. K., A. Khandelwal, N. Pavcnik, and P. Topalova (2010), Multiproduct firms and product turnover in the developing world: Evidence from India, Review of Economics and Statistics, 92(4), Iacovone, L. and B. Javorcik (2010), Multi-product exporters: product churning, uncertainty and export discoveries, Economics Journal, 120 (544), Lau, L. (1976), A Characterization of the Normalized Restricted Profit Function, Journal of Economic Theory, 12, Liu, R. (2010), Import competition and firm refocusing, Canadian Journal of Economics, 43(2), Lopresti, J. (2016), Multiproduct firms and product scope adjustment in trade, Journal of International Economics, 100, Ma, Y., H. Tang, and Y. Zhang (2015), Factor intensity, product switching, and productivity: Evidence from Chinese exporters, Journal of International Economics, 92, Mayer, T., Melitz, M. J., and Ottaviano, G. I. (2011), Market Size, Competition and the Product Mix of Exporters, NBER Working Paper No Nocke, V. and S. Yeaple (2014), Globalization and multi-product firms, International Economic Review, 55, Qiu, L. D. and W. Zhou (2013), Multiproduct firms and scope adjustment in globalization, Journal of International Economics, 91,

25 Figure 1. Development of the average US tariff rates, US Tariff Rates Year Korea MFN Notes: Tariff rates are the average 8-digit (HTS) level US tariff rates from U.S. International Trade Commission. Figure 2. Relationship between tariff rate in 2011 and tariff reduction rate between 2011 and Tariff Tariff difference between 2011 and 2013 Notes: US tariff rate against Korea at 8digit HS code 25

26 Table 1. Prevalence of multi-products, industries, and sectors firms Type of firm Percent of firms Percent of output Mean products, industries, or sectors per firm Multi-product Multi-industry Multi-sector Notes: , , and 2016 data are used. 438,101 manufacturing firms. Table 2. Multi-product versus Single-product firm characteristics Firm characteristic Multi-product Multi-industry Multi-sector Ln(Output) Ln(Employment) Ln(Labor productivity) Ln(TFP) Notes: All the coefficients are statistically significant at 1% level. Year and 4-digit level industry dummies are included in all the estimations. Average percent of sales Table 3. Mean distribution of within-firm sales share Number of products produced by firm Notes: , , and 2016 data are used. 26

27 Table 4. Product churning by Korean manufacturing firms between 2011 and Firm activity All firms Exporters Multi-product Multi-plant Large firms firms firms (Observation) (33,374) (11,008) (5,873) (2,025) (8,402) Panel A. Percent of firms None Drop only Add only Both Panel B. Output-weighted percent of firms None Drop only Add only Both add and drop Notes: Continuing firms between 2011 and 2013 are used. A firm whose number of full-time workers is more than 100 is defined as a large firm. Table 5. Product churning and Tariff differences between before and after Korea-US FTA (1) (2) (3) (4) (5) (6) VARIABLES Add product Drop product ΔTariff (0.012) (0.012) (0.012) (0.012) (0.012) (0.012) Exporter 0.036*** 0.023*** 0.038*** 0.032*** (0.006) (0.007) (0.006) (0.008) ΔTariff * Exporter *** (0.003) (0.002) ln(tfp) 0.016*** 0.015*** 0.014*** 0.013*** 0.011*** 0.011*** (0.004) (0.004) (0.004) (0.004) (0.004) (0.004) Constant 0.130*** 0.126*** 0.132*** 0.136*** 0.132*** 0.134*** (0.029) (0.028) (0.029) (0.029) (0.029) (0.029) Industry FE O O O O O O Observations 33,170 33,170 33,170 33,170 33,170 33,170 R-squared Notes: All columns include 4-digit level industry dummy variables. Numbers in parentheses are standard errors clustered by 4-digit level industry. ***, ** and * indicate statistical significance at the 1%, 5% and 10% levels respectively. 27

28 Table 6. Diversification and Tariff differences between before and after Korea-US FTA (1) (2) (3) (4) (5) (6) VARIABLES Number of products Diversification ΔTariff (0.005) (0.005) (0.005) (0.011) (0.001) (0.001) Exporter 0.025*** 0.017* 0.009*** 0.006*** (0.008) (0.010) (0.002) (0.002) ΔTariff * Exporter * (0.003) (0.001) ln(tfp) 0.016*** 0.015*** 0.014*** 0.003** 0.002** 0.002** (0.004) (0.004) (0.004) (0.011) (0.001) (0.001) Y it *** *** *** *** *** *** (0.021) (0.021) (0.021) (0.007) (0.008) (0.008) Constant * 0.008* 0.009* (0.034) (0.034) (0.034) (0.007) (0.005) (0.005) Industry FE O O O O O O Observations 33,170 33,170 33,170 33,170 33,168 33,168 R-squared Notes: All columns include 4-digit level industry dummy variables. Numbers in parentheses are standard errors clustered by 4-digit level industry. ***, ** and * indicate statistical significance at the 1%, 5% and 10% levels respectively. Table 7. Summary statistics of product characteristics Mean Std. d Min Max ln(relative size) Relative Efficiency Relative Tariff Changes Same Industry Vertically relatedness Notes: Relative size is measured by the share of a product s output to an average product s output in its firm. Vertical relation is defined by using 2010 IO table from Bank of Korea. 28